Dataset Information

Brain natriuretic peptide in acute heart failure and its association with glomerular filtration rate: A systematic review and meta-analysis.

ABSTRACT:

Background

Acute heart failure (AHF) is one of the most common cardiovascular diseases. Early diagnosis and prognosis are essential, as they can eventually lead to a fatal condition. Recently, brain natriuretic peptide (BNP) has been recognized as one of the most popular biomarkers for AHF. Changes in glomerular filtration rate (GFR) are often observed in AHF.

Methods

We searched PubMed, Google Scholar, and ScienceDirect between March and June 2023. Original case control studies written in English that assessed levels oh BNP in AHF were included. Systematic reviews, letters to editor, correspondence, comprehensive reviews, and duplicated studies were excluded. Funnel plots were constructed to assess publication bias.

Results

A total of 9 studies were selected and we obtained the mean difference (MD) of BNP level to be 2.57 (95% CI: 1.35, 3.78), and GFR to be -15.52, (95% CI: -23.35, -7.70) in AHF patients. Sensitivity analyses supported the robustness of the outcome.

Conclusion

Results indicated that BNP was a promising prognostic biomarker of AHF, whereas GFR was found to be negatively correlated with AHF.

SUBMITTER: Mughal HB

PROVIDER: S-EPMC11309607 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature

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Publications

Brain natriuretic peptide in acute heart failure and its association with glomerular filtration rate: A systematic review and meta-analysis.

Mughal Hamdah Bashir HB Majeed Ayesha Isani AI Aftab Maria M Ubaid Muhammad Furqan MF Zahra Sabahat S Abbasi Muhammad Sajid Rafiq MSR Qadir Mamoon M Ahmad Mumtaz M Akbar Amna A Tasneem Sabahat S Jadoon Sarosh Khan SK Tariq Maham M Hussain Saddam S Khandker Shahad Saif SS Alvi Sarosh S

Medicine 20240201 8

<h4>Background</h4>Acute heart failure (AHF) is one of the most common cardiovascular diseases. Early diagnosis and prognosis are essential, as they can eventually lead to a fatal condition. Recently, brain natriuretic peptide (BNP) has been recognized as one of the most popular biomarkers for AHF. Changes in glomerular filtration rate (GFR) are often observed in AHF.<h4>Methods</h4>We searched PubMed, Google Scholar, and ScienceDirect between March and June 2023. Original case control studies w ...[more]

PMID: 38394539

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Project description:BackgroundGreater variability in the estimated glomerular filtration rate (eGFR) is associated with higher mortality in patients with chronic kidney disease (CKD). Heart failure (HF) is common in CKD and may increase variability through changes in hemodynamic and volume regulation. We sought to determine if patients with vs without HF have higher kidney function variability in CKD, and to define the association with mortality.Methods and resultsPatients undergoing coronary angiography from 2003 to 2013 with an eGFR of less than 60 mL/min/1.73 m2 were evaluated from the Duke Databank for Cardiovascular Disease. Variability in the eGFR, measured as the coefficient of variation (CV) of residuals from the regression of eGFR vs time, was calculated spanning 3 months to 2 years after catheterization. Mortality was assessed 2 to 7 years after catheterization. Patients were grouped into 3 HF phenotypes: HF with reduced ejection fraction, HF with preserved ejection, and no HF. Regression was used to evaluate associations between HF phenotypes and variability in the eGFR and between variability in the eGFR and mortality rate with stratification by HF phenotype. Among 3767 participants, the median eGFR at baseline was 45 mL/min/1.73 m2 (interquartile range 33-53 mL/min/1.73 m2), and longitudinal measures of eGFR over 21 months had within-patient residual variability (CV) of 14% (9%-20%). In adjusted analyses, variability in the eGFR was greater in those with HF with preserved ejection (n = 695, CV difference 0.98%, 95% confidence interval 0.14%-1.81%) or HF with reduced ejection fraction (n = 800, CV difference 2.51%, 95% confidence interval 1.66%-3.37%) relative to no HF (n = 2272). In 3068 participants eligible for mortality analysis, the presence of HF and greater variability in the eGFR were each associated independently with higher mortality, but there was no evidence of interaction between variability in the eGFR and any HF phenotype (all P for interaction ≥.49).ConclusionsVariability in the eGFR is greater in patients with HF and associated with mortality. Prediction algorithms and classification schemes should consider not only static, but also dynamic eGFR variability in HF and CKD prognostication.

Project description:AimsThe prognostic significance of renal function variability has not been fully elucidated in heart failure (HF). This multicentre, prospective cohort study aimed to evaluate the usefulness of visit-to-visit variability in estimated glomerular filtration rate (eGFR) for predicting patients' outcomes in a real-world HF population.MethodsA total of 564 patients who had survived HF hospitalization were randomly assigned with a 2:1 ratio to derivation and validation cohorts, and they were then followed after discharge. Using the data for 6 months after discharge, each patient's visit-to-visit eGFR variability (EGV) was estimated. In the derivation cohort, Cox regression analyses were performed to assess the association of EGV with a subsequent composite event (death and HF hospitalization). In the validation cohort, the predictive performance was compared among Cox regression models with EGV, those with B-type natriuretic peptide (BNP) and those with eGFR.ResultsIn the derivation cohort (376 patients), median age, left ventricular ejection fraction (LVEF), BNP and eGFR at discharge were 72 years, 53.3%, 134.8 pg/mL and 58.7 mL/min/1.73 m2 , respectively. During a median follow-up of 2.2 years, higher EGV was associated with an increased risk of the composite event (adjusted hazard ratio [per standard deviation increase in log-transformed EGV], 1.5; 95% confidence interval, 1.1-2.0). A similar finding was observed in a stratified analysis by LVEF. In the validation cohort (188 patients), better model fit, discrimination, reclassification and calibration were observed for EGV than for 6-month averaged BNP or eGFR for predicting the composite event when added to HF risk prediction models. Adding EGV to models with BNP or eGFR improved model discrimination and reclassification.ConclusionsEGV predicts HF outcomes regardless of LVEF. Risk prediction models with EGV have good performance in real-world HF patients. The study findings highlight the clinical importance of observing visit-to-visit fluctuations in renal function in this population.

Dataset Information

Brain natriuretic peptide in acute heart failure and its association with glomerular filtration rate: A systematic review and meta-analysis.

Background

Methods

Results

Conclusion

Publications

Brain natriuretic peptide in acute heart failure and its association with glomerular filtration rate: A systematic review and meta-analysis.

Similar Datasets

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